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Algorithms and complexity for weighted hypergraph embedding in a cycle

机译:循环中加权超图嵌入的算法和复杂性

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The problem of weighted hypergraph embedding in a cycle (WHEC) is to embed the weighted hyperedges of a hypergraph as the paths in a cycle, such that the maximum congestion of any physical link in the cycle is minimized. A simpler version of this problem is the weighted graph embedding in a cycle (WGEC) that embeds the weighted edges of a normal graph as the paths in a cycle. The WHEC and WGEC problems have applications in design automation, parallel computing and computer communication. In this paper we first show that both WHEC and WGEC problems are NP-Complete. Afterwards we formulate the WHEC problem as an integer linear programming (ILP). Therefore, an approximation solution can be obtained by using LP-relaxation and rounding heuristic. Our LP-approximation algorithm generates an embedding with congestion at most two times the optimal solution. Finally, to guarantee the efficiency, we develop a linear-time approximation algorithm that also provides a solution with the same worst case approximation bound as the LP-approximation.
机译:加权超图嵌入循环(WHEC)的问题是将超图的加权超边缘作为循环嵌入路径,以使循环中任何物理链路的最大拥塞减至最小。此问题的一个简单版本是将加权图嵌入循环(WGEC)中,该法则将法线图的加权边作为循环中的路径嵌入。 WHEC和WGEC问题在设计自动化,并行计算和计算机通信中都有应用。在本文中,我们首先证明WHEC和WGEC问题都是NP-Complete。之后,我们将WHEC问题公式化为整数线性规划(ILP)。因此,可以通过使用LP松弛和舍入启发法来获得近似解。我们的LP近似算法生成的拥塞最多是最佳解决方案的两倍。最后,为了保证效率,我们开发了一种线性时间近似算法,该算法还提供了与LP近似具有相同的最坏情况近似范围的解决方案。

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